Measurement of the Higgs boson coupling properties in the H→ZZ*→4ℓ decay channel at s√ = 13 TeV with the ATLAS detector

JHEP03(2018)095 Published for SISSA by Springer Received:December 7, 2017 Revised:March 6, 2018 Accepted:March 7, 2018 Published:March 15, 2018 Measurement of the Higgs boson coupling properties in the H→ZZ∗→4`decay channel at √s= 13 TeV with the ATLAS detector The ATLAS collaboration E-mail: [email protected] Abstract: The coupling properties of the Higgs boson are studied in the four-lepton (e, µ) decay channel using 36.1 fb−1of pp collision data from the LHC at a centre-of-mass energy of 13 TeV collected by the ATLAS detector. Cross sections are measured for the main production modes in several exclusive regions of the Higgs boson production phase space and are interpreted in terms of coupling modifiers. The inclusive cross section times branching ratio for H→ZZ∗decay and for a Higgs boson absolute rapidity below 2.5 is measured to be 1.73+0.24 −0.23(stat.)+0.10 −0.08(exp.)±0.04(th.) pb compared to the Standard Model prediction of 1.34±0.09 pb. In addition, the tensor structure of the Higgs boson couplings is studied using an effective Lagrangian approach for the description of interactions beyond the Standard Model. Constraints are placed on the non-Standard-Model CP-even and CP-odd couplings to Zbosons and on the CP-odd coupling to gluons. Keywords: Hadron-Hadron scattering (experiments) ArXiv ePrint: 1712.02304 Open Access, Copyright CERN, for the benefit of the ATLAS Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP03(2018)095 JHEP03(2018)095 Contents 1 Introduction 1 2 ATLAS detector 2 3 Analysis strategy 3 3.1 Classification of the Higgs boson production modes 3 3.2 Tensor structure of Higgs boson couplings 5 4 Signal and background simulation 6 5 Event selection 8 5.1 Event reconstruction 8 5.2 Selection of the Higgs boson candidates 9 5.3 Categorization of reconstructed Higgs boson event candidates 11 5.4 Additional discriminating observables 13 6 Signal modelling 14 7 Background contributions 15 7.1 Background estimation for the inclusive selection 15 7.2 Background estimation per reconstructed event category 16 8 Systematic uncertainties 17 8.1 Experimental uncertainties 17 8.2 Theoretical uncertainties 19 9 Results 21 9.1 Cross-section measurement by production modes 24 9.2 Tensor structure of Higgs boson couplings to vector bosons 31 10 Summary 34 The ATLAS collaboration 43 1 Introduction The observation of the Higgs boson by the ATLAS and CMS experiments [1,2] with the LHC Run-1 data at centre-of-mass energies of √s = 7 TeV and 8 TeV has been a major step towards the understanding of the mechanism of electroweak (EW) symmetry breaking [3–5]. Further measurements of the spin, parity and couplings of the new particle – 1 – JHEP03(2018)095 have shown no significant deviation from the predictions for the Standard Model (SM) Higgs boson [6–10]. The increased centre-of-mass energy and higher integrated luminosity of the LHC Run-2 data allows the study of the Higgs boson properties in greater detail and an improved search for deviations from the SM predictions. In this paper, the measurement of the Higgs boson coupling properties is performed in the four-lepton decay channel, H→ZZ∗→4`, where `≡eor µ, using 36.1 fb−1of Run-2 pp collision data collected by the ATLAS experiment at a centre-of-mass energy of 13 TeV. This channel provides a clear signature and high signal-to-background ratio. The largest background is the continuum (Z(∗)/γ∗)(Z(∗)/γ∗) production, referred to as ZZ∗hereafter. For the studied four-lepton invariant mass range of 118 GeV < m4`<129 GeV, there are also small but non-negligible background contributions from Z+ jets and t¯ tproduction with two prompt leptons. The Higgs boson spin, parity and coupling properties have been studied in this channel with Run-1 data by the ATLAS and CMS experiments [6,7,11–13]. In this paper, the Higgs boson couplings to SM particles are studied using two analysis approaches. In the first approach, the Higgs boson production cross sections are analyzed based on different production modes in several exclusive regions of the production phase space, testing whether it is compatible with the SM predictions. An interpretation in terms of coupling modifiers within the κframework [14,15] is given, assuming a SM tensor structure (JP= 0+) for all couplings. In the second approach, the tensor structure of the Higgs boson couplings is studied, probing for admixtures of CP-even and CP-odd interactions in theories beyond the SM (BSM) in addition to the corresponding SM interactions. Both analyses are performed assuming that the studied resonance is a single particle state with spin-0 and a mass of 125.09 GeV based on experimental results obtained with the LHC Run-1 data [16]. It is assumed that the total width of the resonance is small compared the experimental resolution and the interference effects between the signal and SM backgrounds are neglected due to the small contribution. The paper is organized as follows. A brief introduction of the ATLAS detector is given in section 2. The analysis strategy describing the two analysis approaches is outlined in section 3. In section 4the data as well as the simulated signal and background samples are described. The selection and categorization of the Higgs boson candidate events, as well as the discriminating observables used in the measurement, are described in section 5, while the signal and background modelling is detailed in sections 6and 7, respectively. The experimental and theoretical systematic uncertainties (section 8) are taken into account for the statistical interpretation of the data, with the results presented in section 9. Concluding remarks are given in section 10. 2 ATLAS detector The ATLAS detector [17] is a multi-purpose particle detector with a forward-backward symmetric cylindrical geometry.1It consists of an inner tracking detector (ID) in a 2 T 1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre 2 JHEP03(2018)095 axial magnetic field covering the pseudorapidity range |η|<2.5. A new innermost silicon pixel layer [18] (IBL) was added to the ID after the Run-1 data-taking. The ID is surrounded by the electromagnetic and hadronic calorimeters up to |η|= 4.9 and by the muon spectrometer (MS) extending up to |η|= 2.7. The magnetic field for the MS is provided by a set of toroids with a field integral ranging between 2 Tm and 6 Tm across most of the detector. The trigger and data-acquisition system is based on two levels of online event selection: a hardware-based first-level trigger and a software-based high-level trigger employing algorithms similar to those for the offline particle reconstruction. 3 Analysis strategy The Higgs boson couplings to heavy SM vector bosons (Wand Z) and gluons are studied by measuring the cross sections for different production modes and by probing BSM contributions in tensor couplings. In both approaches, the reconstructed Higgs boson candidate events are classified into different categories. The categories are defined to be sensitive to different Higgs boson production modes, which in turn also provides sensitivity to the BSM contributions. The event yields in each category serve as the final discriminant for both the cross section and the tensor structure studies. There are nine reconstructed event categories defined for the cross-section measurement, one of which is additionally split into two separate ones for the tensor structure studies to improve their sensitivity. For the crosssection measurement, there are also additional discriminating observables introduced in reconstructed event categories with a sufficiently high number of events. These observables are defined using dedicated boosted decision trees (BDTs) [19]. 3.1 Classification of the Higgs boson production modes The Higgs boson production cross section times the branching ratio of the decay into Z boson pairs, σ·B(H→ZZ∗), is measured in several dedicated mutually exclusive regions of the phase space based on the production process. For simplicity, these regions are called “production bins”. Theoretical uncertainties have a reduced impact on σ·B(H→ZZ∗) results and enter primarily for the interpretation of results in terms of Higgs boson couplings. The definitions of the production bins shown in figure 1(shaded area) are based on particle-level events produced by dedicated event generators closely following the framework of simplified template cross sections [15]. The bins are chosen in such a way that the measurement precision is maximized and at the same time possible BSM contributions can be isolated. All production bins are defined for Higgs bosons with rapidity |yH|<2.5 and no requirements placed on the particle-level leptons. Two sets of production bins are considered since a more inclusive phase-space region usually reduces the statistical uncertainty of the measurement but at the cost of a larger theoretical uncertainty. For the first set (Stage 0) [15], production bins are simply defined according to the Higgs boson production vertex: gluon-gluon fusion (ggF), vector boson fusion (VBF) and of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, with φbeing the azimuthal angle around the beam pipe. The pseudorapidity is defined in terms of the polar angle θas η=−ln tan(θ/2). 3 JHEP03(2018)095 Figure 1. The phase-space regions (production bins) for the measurement of the Higgs boson production cross sections which are defined at the particle level for Stage 0 and 1, and the corresponding reconstructed event categories. Description of production bins is given in section 3, while reconstructed event categories are described in section 5. associated production with top quark pairs (ttH ) or vector bosons (VH ), where Vis a Wor a Zboson. The bbH Higgs boson production bin is not included because there is insufficient sensitivity to measure this process with the current integrated luminosity. This production mode has an acceptance similar to gluon-gluon fusion, and their contributions are therefore considered together in the analysis. The sum of their contributions is referred to in the following as gluon-gluon fusion. For the second set (reduced Stage 1), a more exclusive set of production bins is defined. This set is obtained by the merging of those production bins of the original Stage-1 set from ref. [15] which cannot be measured separately in the H→ZZ∗→4`channel with the current data sample. The gluon-gluon fusion process is split into events with zero, one or at least two particle-level jets. The particle-level jets are built from all stable particles (all particles with cτ > 1 mm) including neutrinos, photons and leptons from hadron decays or produced in the shower. All decay products from the Higgs boson, as well as the leptons and neutrinos from decays of the signal Vbosons are removed, while decay products from hadronically decaying signal Vbosons are included in the inputs to the 4 JHEP03(2018)095 particle-level jet building. The anti-ktjet reconstruction algorithm [20], implemented in the FastJet package [21], with a radius parameter R= 0.4 is used and jets are required to have pT>30 GeV. The 1-jet bin is further split into three bins with the Higgs boson transverse momentum pH Tbelow 60 GeV, between 60 GeV and 120 GeV, and above 120 GeV. The reduced Stage-1 gluon-gluon fusion bins are correspondingly denoted by ggF-0j, ggF- 1j-pH T-Low, ggF-1j-pH T-Med, ggF-1j-pH T-High and ggF-2j. The VBF production bin is split into two bins with the transverse momentum of the leading jet, pj1 T, below and above 200 GeV (VBF-pj T-Low and VBF-pj T-High, respectively). The former bin is expected to be dominated by SM events, while the latter is sensitive to potential BSM contributions. For VH production, separate bins with hadronically (VH -Had) and leptonically (VH -Lep) decaying vector bosons are considered. The leptonic Vboson decays include the decays into τleptons and into neutrino pairs. The ttH production bin remains the same as for Stage 0. Figure 1also summarizes the corresponding categories of reconstructed events in which the cross-section measurements are performed and which are described in more detail in section 5. There is a dedicated reconstructed event category for each production bin except for ggF-2j. This process contributes strongly to all reconstructed event categories containing events with at least two jets, and can therefore be measured in these categories, with the highest sensitivity expected in VBF-enriched-pj T-Low category. 3.2 Tensor structure of Higgs boson couplings In order to study the tensor structure of the Higgs boson couplings to SM gauge bosons, interactions of the Higgs boson with these SM particles are described in terms of the effective Lagrangian of the Higgs characterization model [22], LV 0=κSM 1 2gHZZZµZµ+gHW W W+ µW−µ −1 4hκHgggHggGa µνGa,µν + tan ακAgggAggGa µν ˜ Ga,µνi −1 4 1 ΛhκHZZZµνZµν + tan ακAZZ Zµν ˜ Zµνi −1 2 1 ΛhκHW W W+ µνW−µν + tan ακAW W W+ µν ˜ W−µνiX0.(3.1) The additional terms in the Lagrangian involving couplings to fermions are not considered since the present analysis is not sensitive to these couplings. The model is based on an effective field theory description which assumes there are no new BSM particles below the energy scale Λ. The cut-off scale Λ is set to 1 TeV, supported by the current experimental results showing no evidence of new physics below this scale. The notation of eq. (3.1) follows the notation of eq. (2.4) in ref. [22] with X0defining a new bosonic state of spin 0 and with the difference that the dimensionless coupling parameters κare redefined by dividing them by cos α, where αis the mixing angle between the 0+and 0−CP states implying CP-violation for α6= 0 and α6=π. In this way the prediction for the SM Higgs boson is given by κSM = 1 and κHgg = 1 with the values of the BSM couplings set to zero. In this analysis, only the effective Lagrangian terms with coupling parameters κHV V ,κAV V and 5 JHEP03(2018)095 κAgg are considered as possible BSM admixtures to the corresponding SM interactions. These terms describe the CP-even (scalar) and CP-odd (pseudo-scalar) BSM interaction with vector bosons and the CP-odd BSM interaction with gluons, respectively. The BSM couplings are assumed to be the same for Wand Zbosons (i.e. κHW W =κHZZ ≡κHV V and κAW W =κAZZ ≡κAV V ). The value of αis arbitrarily set to π/4 such that the CP-odd couplings can be more simply denoted by κAV V tan α⇒κAV V and κAgg tan α⇒κAgg. In the previous Run-1 analysis [11], the Higgs-related BSM interactions with heavy vector bosons were studied only in Higgs boson decays. In this analysis, the impact of BSM contributions on both the decay rates and the production cross sections in different production modes is taken into account. The κHV V and κAV V parameters contribute the most to VH and VBF Higgs boson production in the four-lepton decay mode since the coupling is present in both the production and decay vertices. The κAgg parameter mostly affects the ggF production. 4 Signal and background simulation The production of the SM Higgs boson via ggF, VBF and VH (including gg →ZH) production mechanisms was modelled with the POWHEG-BOX v2 Monte Carlo (MC) event generator [23,24], interfaced to EvtGen v1.2.0 [25] for properties of the bottom and charm hadron decays, using the PDF4LHC next-to-leading-order (NLO) set of parton distribution functions (PDF) [26]. The gluon-gluon fusion Higgs boson production is accurate to next- to-next-to-leading order (NNLO) in the strong coupling, using the POWHEG method for merging the NLO Higgs + jet cross section with the parton shower, and the MiNLO method [27] to simultaneously achieve NLO accuracy for inclusive Higgs boson production. A reweighting procedure, employing the Higgs boson rapidity, was applied using the HNNLO program [28,29]. The matrix elements of the VBF and VH production mechanisms were calculated up to NLO in QCD. For VH production, the MiNLO method was used to merge 0- and 1-jet events [30]. The gg →ZH contribution was modelled at leading order (LO) in QCD. The production of a Higgs boson in association with a top (bottom) quark pair was simulated at NLO with MadGraph5 aMC@NLO v2.2.3 (v2.3.3) [31,32], using the CT10nlo PDF set [33] for ttH production and the NNPDF23 PDF set [34] for bbH production. For the ggF, VBF, VH and bbH production mechanisms, the PYTHIA 8 [35] generator was used for the H→ZZ∗→4`decay as well as for the parton shower model using a set of tuned parameters called the AZNLO tune [36]. For the ttH production mechanism, the Herwig++ [37] event generator was used with the UEEE5 tune [38]. All signal samples were simulated for the Higgs boson with a mass mH= 125.00 GeV. Wherever relevant, the signal mass distribution is shifted to the reference value of 125.09 GeV. The Higgs boson production cross sections and decay branching ratios, as well as their uncertainties, were taken from refs. [14,26,34,39–66]. The ggF production was calculated with next-to-next-to-next-to-leading order (N3LO) accuracy in QCD and has NLO electroweak (EW) corrections applied. For VBF production, full NLO QCD and EW calculations were used with approximate NNLO QCD corrections. The VH production was calculated at NNLO in QCD and NLO EW corrections are applied. The ttH and 6 JHEP03(2018)095 Production process σ[pb] ggF (gg →H) 48.5±2.4 VBF (qq0→Hqq0) 3.78 ±0.08 WH q¯ q0→WH1.369 ±0.028 ZH (q¯q/gg →ZH) 0.88 ±0.04 ttH (q¯q/gg →t¯ tH) 0.51 ±0.05 bbH q¯q/gg →b¯ bH0.49 ±0.12 Decay process B[·10−4] H→ZZ∗264 ±6 H→ZZ∗→4`1.250 ±0.027 Table 1. The predicted SM Higgs boson production cross sections (σ) for ggF, VBF and associated production with a Wor Zboson or with a t¯ tor b¯ bpair in pp collisions for mH= 125.09 GeV at √s = 13 TeV [14,26,34,39–66]. The quoted uncertainties correspond to the total theoretical systematic uncertainties calculated by adding in quadrature the QCD scale and PDF+αsuncertainties. The decay branching ratio (B) with the associated uncertainty for H→ZZ∗and H→ZZ∗→4`with `=e, µ, is also given. bbH processes were calculated to NLO accuracy in QCD. The branching ratio for the H→ZZ∗→4`decay with mH= 125.09 GeV was predicted to be 0.0125% [60] in the SM using PROPHECY4F [62,63], which includes the complete NLO QCD and EW corrections, and the interference effects between identical final-state fermions. Table 1 summarizes the production cross sections and branching ratios for the H→ZZ∗→4` decay for mH= 125.09 GeV. Additional ggF, VBF and VH signal samples with different values of the BSM couplings κAgg,κHV V and κAV V were generated with MadGraph5 aMC@NLO and are used for the signal modelling as a function of the BSM couplings as explained in section 6. The ggF simulation includes samples at NLO QCD accuracy for zero, one and two additional partons merged with the FxFx merging scheme [31,67], while the VBF and VH simulations are accurate to LO in αs. Equivalent VBF and VH processes were also generated at NLO QCD accuracy and used to estimate the relative uncertainties of higher-order QCD effects as a function of the BSM coupling parameters. The ZZ∗continuum background from quark-antiquark annihilation was modelled using Sherpa 2.2.2 [68–70], which provides a matrix element calculation accurate to NLO in αs for 0-, and 1-jet final states and LO accuracy for 2- and 3-jet final states. The merging was performed with the Sherpa parton shower [71] using the ME+PS@NLO prescription [72]. The NLO EW corrections were applied as a function of the invariant mass of the ZZ∗ system mZZ∗[73,74]. The gluon-induced ZZ∗production was modelled by gg2VV [75] at LO in QCD. The higher-order QCD effects for the gg →ZZ∗continuum production have been calculated for massless quark loops [76–78] in the heavy top-quark approximation [79], including the gg →H∗→ZZ processes [80,81]. The simulated LO samples are scaled by the K-factor 7 JHEP03(2018)095 of 1.7±1.0, defined as the ratio of the higher-order and the leading-order cross section predictions. The WZ background was modelled using POWHEG-BOX v2 interfaced to PYTHIA 8 and EvtGen v1.2.0 for properties of the bottom and charm hadron decays. The triboson backgrounds ZZZ,WZZ, and WWZ with four or more prompt leptons were modelled using Sherpa 2.1.1. The simulation of t¯ t+Zevents with both top quarks decaying semi-leptonically and the Z boson decaying leptonically was performed with MadGraph interfaced to PYTHIA 8 and the total cross section was normalized to the prediction which includes the two dominant terms at both the LO and the NLO in a mixed perturbative expansion in the QCD and EW couplings [56]. The modelling of events containing Zbosons with associated jets was performed using the Sherpa 2.2.2 generator. Matrix elements were calculated for up to two partons at NLO and four partons at LO using Comix [69] and OpenLoops [70], and merged with the Sherpa parton shower [71] using the ME+PS@NLO prescription [72]. The NNPDF3.0 NNLO PDF set was used in conjunction with dedicated parton shower parameters tuning developed by the Sherpa authors. Simulated samples were normalized to the data-driven estimate described in section 7. As a cross-check, this estimate was compared to the theory prediction obtained with FEWZ [82,83] at NNLO in αs. The t¯ tbackground was modelled using POWHEG-BOX v2 interfaced to PYTHIA 6 [84] for parton showering, hadronisation, and the underlying event and to EvtGen v1.2.0 for properties of the bottom and charm hadron decays. Generated events were processed through the ATLAS detector simulation [85] within the Geant4 framework [86] and reconstructed the same way as the data. Additional pp interactions in the same and nearby bunch crossings (pile-up) are included in the simulation. The pile-up events were generated using PYTHIA 8 with the A2 set of tuned parameters [87] and the MSTW2008LO PDF set [88]. The simulation samples were weighted to reproduce the observed distribution of the mean number of interactions per bunch crossing in the data. 5 Event selection 5.1 Event reconstruction The selection and categorization of the Higgs boson candidate events rely on the reconstruction and identification of electrons, muons and jets, closely following the analyses reported in refs. [11,89]. Collision vertices are reconstructed from ID tracks with transverse momentum pT>400 MeV. The vertex with the highest Pp2 Tof reconstructed tracks is selected as the primary vertex. Events are required to have at least one collision vertex with at least two associated tracks. Electron candidates are reconstructed from ID tracks that are matched to energy clusters in the electromagnetic calorimeter [90]. A Gaussian-sum filter algorithm [91] is used to compensate for radiative energy losses in the ID. Electron identification is based on a likelihood discriminant combining the measured track properties, electromagnetic shower 8 JHEP03(2018)095 there is little sensitivity to ttH production in the H→ZZ∗→4`channel, it is assumed that the production vertex of the ttH and bbH processes is not affected by the BSM parameters. The impact of the BSM parameters on the Higgs boson decay is accounted for by scaling the corresponding decay branching ratio. The BSM parameters also affect B(H→Zγ) and B(H→γγ) but the impact on the signal model predictions is found to be negligible and is not considered in the analyses. 7 Background contributions The main source of background in the H→ZZ∗→4`decay channel is non-resonant ZZ∗production with the same final state as the signal. This process, as well as a minor contribution from t¯ tV and triboson production, is modelled using simulation normalized to the highest-order SM prediction available. Additional reducible background sources are the Z+jets, t¯ tand WZ processes whose contributions in the signal region (SR) are estimated using dedicated signal-depleted control regions (CRs) in data, separately for events with different flavours of the subleading lepton pair (i.e. `` +µµ or `` +ee, where `` denotes the leading and µµ or ee the subleading lepton pair). No requirement is imposed on the four-lepton invariant mass in the control data. The backgrounds are first estimated for the inclusive event selection, i.e. prior to event categorization, and then divided into separate contributions in each reconstructed event category. 7.1 Background estimation for the inclusive selection The reducible `` +µµ background with at least one jet containing a muon from secondary decays of pions/kaons or heavy-flavour hadrons originates from Z+jets, t¯ tand WZ production. The Z+jets background comprises a heavy-flavour (Z+HF) component containing jets with b- or c-quark content and a light-flavour (Z+LF) component from pion or kaon decays. These components of the Z+jets background and the t¯ tcontribution are extracted using orthogonal CRs formed by relaxing the χ2requirement on the vertex fit, and by inverting or relaxing isolation and/or impact parameter requirements on the subleading muon pair. In these regions an unbinned maximum-likelihood fit to m12 is performed. The numbers of t¯ t,Z+HF and Z+LF events estimated in these CRs are each extrapolated to the SR using a simulation-based transfer factor which depends on the efficiency of the isolation and impact parameter selection criteria. The contribution from WZ production is estimated using simulation. The reducible `` +ee background originating mainly from the Z+jets, t¯ tand WZ production is classified into processes with misidentified jets faking an electron (f), electrons from photon conversions (γ) and electrons from semileptonic decays of heavy quarks (q). The contribution of the qcomponent is obtained from simulation, while the fand the γ components are obtained from the 3`+XCR containing 2µ2eand 4efinal states. In this CR, three leptons pass the full analysis selection, while the most probable candidate for a fake electron, the lowest-ETelectron (denoted by X) in the subleading electron pair, has only the track hit requirement of the electron identification applied. In order to suppress 15 JHEP03(2018)095 the ZZ∗contribution, only electrons with same-sign charge are considered for the subleading electron pair in this CR. A template fit to the number of track hits (nInnerPix) in the innermost or next-to-innermost2pixel layer for the associated track is used to separate the γand fbackground components. The templates for the γand fbackground contributions are obtained from simulated Z+Xevents with an on-shell Zboson decay candidate accompanied by an electron Xselected using the same criteria as in the 3`+XCR. The simulated Z+Xevents are also used to obtain the efficiencies needed to extrapolate the fand γbackground contributions from the CR to the SR, after correcting the simulation to match the data in dedicated control samples of Z+Xevents. 7.2 Background estimation per reconstructed event category The background event yields and BDT output distributions are determined separately for each event category. The reducible `` +ee background normalization is obtained by applying the data-driven approach described above for the inclusive sample in each separate category. The fraction of the reducible ``+µµ background per category with respect to the inclusive yield is obtained from simulation, separately for the Z+jets and t¯ tbackground. The ``+µµ simulation was checked against data in CRs with relaxed selection criteria and is found to predict the fraction of reducible background events in each category well within the statistical uncertainty. Since the data-driven background estimates provide the event yields for the full m4` range, the effect of the m4`mass window requirement has to be taken into account. For this purpose, the m4`distributions of reducible backgrounds in each category are smoothed with the kernel density estimation method [101] and then integrated to obtain the fraction of events within the mass window. The yields of the backgrounds in each category are shown in table 4, together with the associated systematic uncertainties. Three sources of uncertainty are considered. First, the systematic uncertainty of the inclusive background estimate from the determination of the selection efficiencies related to the lepton identification, isolation and impact parameter significance. This uncertainty is evaluated by comparing data with an on-shell Zboson decay candidate accompanied by an electron or a muon to the simulation. Second, the inclusive background estimate has also a relatively small (4%) statistical uncertainty from the control data. The total uncertainty of the inclusive reducible background estimate from both of these sources is considered as correlated across the experimental categories. Third, there is an additional uncorrelated uncertainty in the fraction of the reducible background in each experimental category due to the statistical precision of the simulated samples. The shapes of the BDT discriminant distributions for the reducible background are determined from simulation by combining the simulated t¯ tand Z+jets distributions according to the relative fractions measured in data. To increase the statistical precision of the simulated samples, the isolation requirements and m4`range are relaxed. The mass window requirement is relaxed in the 0jcategory to 115 < m4`<130 GeV and to 2A hit in the next-to-innermost pixel layer is used when the electron falls in a region that is either not instrumented with an IBL module or the IBL module is not operating. 16 JHEP03(2018)095 Reconstructed Reducible background Uncertainty event category ``+µµ ``+ee Total Corr. Uncorr. 0j0.96 ±0.21 1.25 ±0.23 2.21 ±0.33 ±13% ±7% 1j-p4` T-Low 0.21 ±0.05 0.30 ±0.06 0.52 ±0.08 ±13% ±10% 1j-p4` T-Med 0.19 ±0.12 0.16 ±0.04 0.35 ±0.13 ±13% ±40% 1j-p4` T-High 0.0049 ±0.0025 0.036 ±0.008 0.041 ±0.009 ±13% ±18% VBF-enriched-pj T-Low 0.14 ±0.04 0.128 ±0.025 0.27 ±0.05 ±13% ±15% VBF-enriched-pj T-High 0.019 ±0.010 0.018 ±0.004 0.037 ±0.009 ±13% ±28% VH -Had-enriched-p4` T-Low 0.057 ±0.015 0.067 ±0.015 0.124 ±0.021 ±13% ±14% VH -Had-enriched-p4` T-High 0.0035 ±0.0023 0.011 ±0.004 0.015 ±0.004 ±13% ±34% VH -Lep-enriched 0.003 ±0.004 0.0005 ±0.0008 0.0031 ±0.0031 ±13% ±100% ttH -enriched 0.009 ±0.004 0.022 ±0.005 0.031 ±0.007 ±13% ±22% Table 4. Estimates of reducible background yields in each reconstructed event category in the signal region for 36.1 fb−1at √s = 13 TeV, together with the associated correlated and uncorrelated systematic uncertainties. The total error in each category is composed of the combined statistical and systematic uncertainty of the inclusive background estimate, as well as an additional statistical uncertainty in the fraction of the reducible background in each category. The uncertainty due to the inclusive background estimate is considered as correlated (penultimate column), while the statistical uncertainty due to the event categorization (last column) is uncorrelated across the reconstructed event categories. 110 < m4`<200 GeV for all other categories. Instead of both leptons, at least one lepton in the subleading pair is required to meet the isolation criteria. These looser selection criteria have no impact on the shape of the BDT distributions. The statistical precision of the simulated samples and the uncertainty in the relative fractions of Z+jets and t¯ t contributions are taken into account as systematic shape variations. 8 Systematic uncertainties The systematic uncertainties in this analysis are grouped into experimental and theoretical uncertainties. The first category includes uncertainties in the modelling of lepton and jet reconstruction, identification efficiencies, energy resolution and scale, and in the total integrated luminosity. Uncertainties from the procedure used to derive the data-driven background estimates are also included in this category. The second category includes uncertainties in the theoretical modelling of the signal and the background processes. The uncertainties can affect the signal acceptance, efficiency and discriminant distributions as well as the background estimates. The dominant sources of uncertainty and their effect are described in the following subsections. The impact of these uncertainties on the cross-section measurements in different production bins is summarized in table 5. 8.1 Experimental uncertainties The uncertainty in the combined 2015+2016 integrated luminosity is 3.2%. It is derived, following a methodology similar to the one described in ref. [102], from a preliminary 17 JHEP03(2018)095 Experimental uncertainties [%] Theory uncertainties [%] Production Lumi e,µ, Jets, flavour Higgs Reducible ZZ∗Signal theory bin pile-up tagging mass backgr. backgr. PDF QCD scale Shower Inclusive cross section 4.1 3.1 0.7 0.8 0.9 1.9 0.3 0.8 1.2 Stage-0 production bin cross sections ggF 4.3 3.4 1.1 1.2 1.1 1.8 0.5 1.8 1.4 VBF 2.6 2.7 10 1.3 0.9 2.2 1.6 11 5.3 VH 3.0 2.7 11 1.6 1.7 5.9 2.1 12 3.7 ttH 3.6 2.9 19 <0.1 2.4 1.9 3.3 7.9 2.1 Table 5. Impact of the dominant systematic uncertainties (in percent) on the measured inclusive and the Stage-0 production mode cross sections σ·B(H→ZZ∗). Signal theory uncertainties include only acceptance effects and no uncertainty in predicted cross sections. calibration of the luminosity scale using x–ybeam-separation scans performed in August 2015 and May 2016. The uncertainty in the predicted yields due to pile-up modelling is about 2% and is derived by varying the average number of pile-up events in the simulation to cover the uncertainty in the ratio of the predicted to measured inelastic cross sections [103]. The electron (muon) reconstruction and identification efficiencies, and the energy (momentum) scale and resolution are derived from data using large samples of J/ψ →`` and Z→`` decays [91–93]. Typical uncertainties in the predicted yield due to the identification efficiencies are in the range 0.5–1.0% for muons and 1.0–1.3% for electrons. The uncertainty in the expected yields coming from the muon and electron isolation efficiencies are also taken into account, with the typical size being 2%. The uncertainties in the electron and muon energy scale and resolution are small and have a negligible impact on the measurements presented in section 9. The uncertainties in the jet energy scale and resolution are in the range of 3–7% and 2– 4%, respectively [104,105]. Given the analysis categories, the impact of these uncertainties are more relevant for the VH , VBF and ttH production modes cross-section measurements (10–20%) and for all the reduced Stage-1 cross-section measurements, including the ggF process split into the different n-jet exclusive production bins (5–20%), while they are negligible for the inclusive and the ggF (Stage-0) cross-section measurements. The uncertainties associated with the efficiency of the b-tagging algorithm, which are derived from t¯ tevents, are at the level of a few percent over most of the jet pTrange [97]. This uncertainty is only relevant in the ttH -enriched category, with its expected impact being approximately 5% in the ttH cross-section measurement. The impact of the precision of the Higgs boson mass measurement, mH= 125.09 ± 0.24 GeV [16], on the signal acceptance due to the mass window requirement defining the signal region is negligible. A small dependency of the BDTggF shape on mHis observed for the signal (below 2% in the highest BDT bins) and is included in the signal model. This uncertainty affects the measurement of ggF production, as well as the measurements in other production bins with large ggF contamination. 18 JHEP03(2018)095 The uncertainties from the data-driven measurement of reducible background contributions are detailed in section 7. Their impact on the cross-section measurements is also summarized in table 5. 8.2 Theoretical uncertainties The theoretical modelling of the signal and background processes is affected by uncertainties from QCD scale variations, modelling of parton showers and multiple-particle interactions, and PDF uncertainties. The impact of the theory systematic uncertainties on the signal depends on the kind of measurement that is performed. For the signal strength measurements and the tensor structure analysis, each source of theory uncertainty affects both the fiducial acceptance and the predicted SM cross section. For the cross-section measurements, only effects on the acceptance need to be considered. One of the dominant sources of theoretical uncertainty is the prediction of the ggF process in the different n-jet categories. The ggF process is the major background in the 2-jet categories that are used to measure the cross section of the VBF and VH production modes. To estimate the QCD scale variation and migration effects on the n-jet ggF cross sections, the approach described in ref. [15] is used, which exploits the latest predictions for the inclusive jet cross sections and the exclusive jet bin fractions. In particular, the uncertainty from the choice of the factorization and renormalization scales, the choice of resummation scales, and the migrations between the 0-jet and 1-jet phase-space bins or between the 1-jet and ≥2-jet bins are considered. The impact of QCD scale variations on the Higgs boson pTdistribution is taken into account as an additional uncertainty. The uncertainty in the Higgs boson pTat higher order originating from the assumption of infinite top and bottom quark masses in the heavy-quark loop is also taken into account by comparing the pTdistribution predictions to finite-mass calculations. An additional uncertainty in the acceptance of the ggF process in VBF topologies due to missing higher orders in QCD in the calculation is estimated by variations of the resummation and factorization scales using fixed-order calculations with MCFM [106]. For the other production modes, the QCD scale uncertainties are obtained by varying the scale by factors of two. The configuration with the largest impact is chosen to define the uncertainty in each experimental category as the relative difference between the prediction in this and the nominal configuration. QCD scale uncertainties are treated as uncorrelated among the different production modes. The uncertainties in the acceptances due to the modelling of parton showers and multiple-parton interactions are estimated with AZNLO tune eigenvector variations and by comparing the acceptance using the parton showering algorithm from PYTHIA 8 with Herwig7 for the ggF, VBF and VH processes, while Herwig++ is compared with PYTHIA 8 for the ttH process. The uncertainty due to each AZNLO tune variation is taken as correlated among the different production modes while the difference between the parton showering algorithms is treated as an uncorrelated uncertainty. Uncertainties due to the modelling of the ggF production in association with b-quarks affect the measurement in the ttH production bin only negligibly compared to the statistical precision. They are therefore not taken into account for the final result. 19 JHEP03(2018)095 The impact of the PDF uncertainties is estimated with the eigenvector variations of the PDF4LHC nlo 30 Hessian PDF set. The modification of the predictions for each eigenvector variation is added as a separate source of uncertainty in the model. The same procedure is applied for the ggF, VBF and VH processes, enabling correlations to be taken into account in the fit model. The same procedure is used to estimate the impact of the sources of theoretical uncertainty described above on the shape of BDT discriminants. In addition, for VBF Higgs production, the changes in the ∆ηjj distribution as predicted at NNLO compared to NLO in QCD [107] are considered and shown to have a negligible impact on the BDT distributions. For ggF production, a further cross-check is performed by comparing the BDT1j-p4` T-Low VBF , BDT1j-p4` T-Med VBF , BDTVBF and BDTV H-Had shapes in the corresponding categories as predicted by Powheg NNLOPS and MadGraph5 aMC@NLO (with the FxFx merging scheme). The BDT shapes from the two generators agree within the statistical uncertainties and, therefore, no additional shape uncertainty is included. For BSM interactions parameterized via the effective Lagrangian terms, the theoretical uncertainties in the PDF set and the missing higher-order QCD and EW corrections are generally assumed to factorize with respect to the new physics. However, it has been shown [108] that the K-factors corresponding to the NLO to LO cross-section ratio, as well as several kinematic quantities that affect the categorization of reconstructed events, such as the jet transverse momenta, receive higher-order corrections that can differ from those computed for the SM process and depend on the value of the BSM couplings. Therefore, an uncertainty is assigned to the K-factor obtained from the SM samples. For this purpose, the K-factor for a given VBF and VH BSM process is evaluated as the ratio of NLO to LO event yields in simulated BSM samples, separately for each reconstructed event category. The uncertainty in the SM K-factor is then defined as the relative difference of the K-factors computed for the BSM and SM processes. The obtained uncertainties range from 10% to 40% depending on the category and are considered as being correlated across all categories. This is one of the dominant sources of uncertainty for the tensor structure measurements. No such uncertainty is considered for the ggF BSM samples as these are simulated at NLO. The dominant theoretical uncertainty in the expected ZZ∗background yield in the signal mass window is obtained by varying the factorization and renormalization QCD scales by factors of two. The configuration with the largest impact is chosen to define the uncertainty in each experimental category as the relative difference between the prediction in this and the nominal configuration. This uncertainty is about 4% for the inclusive event yield and is as large as 30% for the categories where additional jets are required. The impact of the QCD scale uncertainty on the BDT discriminant shapes is approximately 1–2%. The PDF uncertainty on the ZZ∗event yield in each category and on the BDT distributions, obtained using the MC replicas of the NNPDF3.0 PDF set, was found to be approximately 1–2%. The impact of the parton shower modelling uncertainty on the ZZ∗event yield is estimated to be approximately 1–5%, with the largest value reached in the categories where the presence of one or more jets is required. In addition, the event yield and BDT discriminant shapes in each event category are compared to the data in a 20 JHEP03(2018)095 [GeV] Constrained 4l m 80 100 120 140 160 Events / 2.5 GeV 0 10 20 30 40 50 60 Data = 125.09 GeV) H (mHiggs ZZ* +V, VVV tt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb Figure 3. The expected and observed four-lepton invariant mass distribution for the selected Higgs boson candidates with a constrained Zboson mass, shown for an integrated luminosity of 36.1 fb−1and at √s = 13 TeV assuming the SM Higgs boson signal with a mass mH= 125.09 GeV. sideband around the signal region (m4l<115 GeV or 130 GeV< m4l<170 GeV). Good agreement between the Sherpa predictions and the data is found. 9 Results The expected and observed four-lepton invariant mass distribution of the selected Higgs boson candidates after the event selection with a constrained Zboson mass is shown in figure 3. The corresponding expected and observed numbers of events are shown in table 6separately for each of the four decay channels. The predicted event yields are in reasonable agreement with the data. The observed and expected distributions of the jet multiplicity, the dijet invariant mass, as well as the leading jet and the four-lepton transverse momenta, which are used for the categorization of reconstructed events, are shown in figure 4for different stages of the event categorization. As shown in figures 4(c) and 4(d) there is an excess of events observed in the sample with ≥2 jets (shown as a dijet invariant mass distribution) and also in the subset with mjj >120 GeV (shown as the jet pTdistribution) in comparison with the expectations. All other distributions are in good agreement with the data. The expected numbers of signal and background events in each reconstructed event category (including the splitting of the VH -enriched category for the tensor structure measurement) are shown in table 7together with the corresponding observed number of events. The expected event yields are in reasonable agreement with the observed ones. The largest differences are again observed in the two VBF-enriched categories. The expected and observed distributions of the BDT discriminants introduced in section 5.4 are shown in figure 5, where a small excess is observed at larger values of 21 JHEP03(2018)095 Decay Signal Signal ZZ∗Other Total Observed channel (full mass range) background backgrounds expected 4µ21.0±1.7 19.7±1.6 7.5±0.6 1.00 ±0.21 28.1±1.7 32 2e2µ15.0±1.2 13.5±1.0 5.4±0.4 0.78 ±0.17 19.7±1.1 30 2µ2e11.4±1.1 10.4±1.0 3.57 ±0.35 1.09 ±0.19 15.1±1.0 18 4e11.3±1.1 9.9±1.0 3.35 ±0.32 1.01 ±0.17 14.3±1.0 15 Total 59 ±5 54 ±4 19.7±1.5 3.9±0.5 77 ±4 95 Table 6. The expected and observed numbers of signal and background events in the four-lepton decay channels for an integrated luminosity of 36.1 fb−1and at √s = 13 TeV, assuming the SM Higgs boson signal with a mass mH= 125.09 GeV. The second column shows the expected number of signal events for the full mass range while the subsequent columns correspond to the mass range of 118 < m4`<129 GeV. In addition to the ZZ∗background, the contribution of other backgrounds is shown, comprising the data-driven estimate from table 4and the simulation-based estimate of contributions from rare triboson and t¯ tV processes. Statistical and systematic uncertainties are added in quadrature. Reconstructed Signal ZZ∗Other Total Observed event category background backgrounds expected 0j26.8±2.5 13.7±1.0 2.23 ±0.31 42.7±2.7 49 1j-p4` T-Low 8.8±1.1 3.1±0.4 0.53 ±0.07 12.5±1.2 12 1j-p4` T-Med 5.4±0.7 0.88 ±0.12 0.38 ±0.05 6.7±0.7 9 1j-p4` T-High 1.47 ±0.24 0.139 ±0.022 0.045 ±0.007 1.65 ±0.24 3 VBF-enriched-pj T-Low 6.3±0.8 1.08 ±0.32 0.40 ±0.04 7.7±0.9 16 VBF-enriched-pj T-High 0.58 ±0.10 0.093 ±0.032 0.054 ±0.006 0.72 ±0.10 3 VH -Had-enriched-p4` T-Low 2.9±0.5 0.63 ±0.16 0.169 ±0.021 3.7±0.5 3 VH -Had-enriched-p4` T-High 0.64 ±0.09 0.029 ±0.008 0.0182 ±0.0022 0.69 ±0.09 0 VH -Lep-enriched 0.318 ±0.019 0.049 ±0.008 0.0137 ±0.0019 0.380 ±0.020 0 ttH -enriched 0.39 ±0.04 0.014 ±0.006 0.07 ±0.04 0.47 ±0.05 0 Total 54 ±4 19.7±1.5 3.9±0.5 77 ±4 95 Table 7. The expected and observed numbers of signal and background events in the mass range 118 < m4`<129 GeV for an integrated luminosity of 36.1 fb−1and at √s = 13 TeV in each reconstructed event category (including the splitting of the VH -enriched category for the tensor structure measurement), assuming the SM Higgs boson signal with a mass mH= 125.09 GeV. In addition to the ZZ∗background, the contribution of other backgrounds is shown, comprising the data-driven estimate from table 4and the simulation-based estimate of contributions from rare triboson and t¯ tV processes. Statistical and systematic uncertainties are added in quadrature. 22 JHEP03(2018)095 Jets N 0 1 2 3 4 Events 0 10 20 30 40 50 60 70 80 Data ggF VBF VH ttH ZZ* +V, VVVtt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb < 129 GeV l4 118 < m Inclusive (a) [GeV] 4l T p 0 50 100 150 200 Events / 20 GeV 0 2 4 6 8 10 12 14 16 18 Data VBF ggF VH ttH ZZ* +V, VVVtt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb < 129 GeV l4 118 < m = 1 jet N (b) [GeV] jj m 0 500 1000 1500 2000 Events / 200 GeV 0 2 4 6 8 10 12 14 16 18 Data VBF ggF VH ttH ZZ* +V, VVVtt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb < 129 GeV l4 118 < m 2≥ jets N (c) [GeV] j1 T p 50 100 150 200 250 300 350 400 Events / 40 GeV 0 2 4 6 8 10 12 14 16 Data VBF ggF VH ttH ZZ* +V, VVVtt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb < 129 GeV l4 118 < m > 120 GeV jj 2, m≥ jets N (d) [GeV] 4l T p 0 50 100 150 200 Events / 20 GeV 0 1 2 3 4 5 6Data VH ggF VBF ttH ZZ* +V, VVVtt tZ+jets, t Uncertainty ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb < 129 GeV l4 118 < m < 120 GeV jj 2, m≥ jets N (e) Figure 4. The observed and expected distributions of (a) Njet after the inclusive selection, (b) p4l Tin the 1-jet categories, (c) mjj in the 2-jet categories, (d) pj1 Tin the VBF-enriched categories and (e) p4l Tin the VH -Had-enriched categories for an integrated luminosity of 36.1 fb−1collected at √s = 13 TeV assuming the SM Higgs boson signal with a mass mH= 125.09 GeV. 23 JHEP03(2018)095 the VBF BDT. All other distributions are in good agreement with the data. Based on these results, the measurements of the Higgs boson production cross sections and of its tensor coupling structure are performed. The profile likelihood ratio [109] is used for the interpretation of data with the effects of systematic uncertainties included as constrained nuisance parameters. If the same source of uncertainty affects two or more processes (e.g. the error in the integrated luminosity can affect the signal yield and the MC-based background estimates), the same nuisance parameter is assigned to each of these processes. 9.1 Cross-section measurement by production modes In order to measure the Higgs boson production cross section times branching ratio for H→ZZ∗decay for each Stage-0 or reduced Stage-1 production bin, a fit to the data is performed using the likelihood function L(~σ, ~ θ) that depends on the Higgs boson production cross section ~σ ={σ1, σ2, . . . , σN}in each production bin and the nuisance parameters ~ θ accounting for the systematic uncertainties. The likelihood function is defined as a product of conditional probabilities Pover binned distributions of the discriminating observables in each reconstructed event category j, L(~σ, ~ θ) = Ncategories Y j Nbins Y i PNi,j |L·~σ ·~ Ai,j(~ θ) + Bi,j (~ θ)× Nnuisance Y mCm(~ θ), with Poisson distributions Pcorresponding to the observation of Ni,j events in each bin iof the discriminating observable given the expectations for the background, Bi,j(~ θ), and for the signal, Si,j(~ θ) = L·~σ ·~ Ai,j(~ θ), where Lis the integrated luminosity and ~ Ai,j(~ θ) the signal acceptance in each production bin. The signal acceptance is defined as the number of simulated signal events satisfying the event selection criteria in a given reconstructed event category divided by the total number of events generated in the phase space defined by the production bin. Constraints on the nuisance parameters corresponding to systematic uncertainties described in section 8are represented by the functions Cm(~ θ). The cross sections are treated as independent parameters for each production bin and correlated among the different categories. The test statistic used to compare the probabilities of different hypotheses is the ratio of profile likelihoods [109], q=−2 ln L(~σ, ˆ ˆ ~ θ(~σ)) L(ˆ ~σ, ˆ ~ θ) =−2 ln λ(~σ), where ~σ represents only the cross section(s) considered as parameter(s) of interest in the given fit, while the likelihood is maximized with respect to all remaining cross sections and nuisance parameters. In the denominator the likelihood is maximized with respect to all other cross sections and nuisance parameters as well as the parameters of interest, which are fixed to hypothetical values in the numerator. The parameter of interest σ in each production bin is alternatively replaced by µ·σSM(~ θ), allowing an interpretation in terms of the signal strength µrelative to the SM prediction σSM(~ θ). In addition, the number of signal events is extracted from a simultaneous fit of the signal templates in all 24 JHEP03(2018)095 [pb]B⋅ VBF σ 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 [pb]B⋅ ggF σ 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb Best Fit 68% CL Obs. 95% CL Obs. SM (a) V κ 0 0.5 1 1.5 2 F κ 0 0.5 1 1.5 2 2.5 3 3.5 ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb Best Fit 68% CL Obs. 95% CL Obs. SM (b) Figure 8. (a) Likelihood contours at 68% CL (dashed line) and 95% CL (solid line) in the (σggF ·B, σVBF ·B) plane and (b) likelihood contours in the κV–κFplane. The best fits to the data (solid cross) and the SM predictions are also indicated. In (a), the SM prediction is shown together with its theory uncertainty (filled blue elipse), while in (b) only the central value of the SM prediction (solid blue star) is shown. 9.2 Tensor structure of Higgs boson couplings to vector bosons In order to probe the tensor structure of the Higgs boson couplings to vector bosons, a likelihood function is constructed as a product of conditional probabilities over the event yield Njin each reconstructed event category j, L(~κ, ~ θ) = Ncategories Y j PNj|S(~κ) j(~ θ) + Bj(~ θ)× Nnuisance Y mCm(~ θ), with the set of coupling parameters ~κ representing the parameters of interest for a specific hypothesis test. The expected number of signal events S(~κ) j(~ θ) is parameterized in terms of the SM and BSM couplings using the signal modelling described in section 6, while the expected background event yields Bj(~ θ) are given by the background estimates detailed in section 7. As in the case of the cross-section measurements, the test statistic is based on a profile likelihood ratio, q=−2 ln L(~κ, ˆ ˆ ~ θ(~κ)) L(ˆ ~κ, ˆ ~ θ(ˆ ~κ)) =−2 ln λ(~κ), with the conditional and the unconditional maximum-likelihood estimators in the numerator and the denominator, respectively. The coupling parameter κAgg is measured assuming that all other BSM couplings are equal to zero. The coupling parameters κHV V and κAV V are probed both simultaneously and one at a time assuming that all other BSM couplings 31 JHEP03(2018)095 Agg κ 1−0.5−0 0.5 1 )λ -2ln ( 0 5 10 15 20 25 68% CL 95% CL Observed SM expected ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb = 1 SM κ = 1, Hgg κ | = 0.43 Agg κ Observed: | = 0.00 Agg κ Expected: (a) Hvv κ 6−4−2−0 2 4 6 )λ -2ln ( 0 5 10 15 20 25 30 68% CL 95% CL Observed SM expected ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb = 1 SM κ = 1, Hgg κ = 2.9 Hvv κ Observed: = 0.0 Hvv κ Expected: (b) Avv κ 8−6−4−2−0 2 4 6 8 )λ -2ln ( 0 5 10 15 20 25 30 68% CL 95% CL Observed SM expected ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb = 1 SM κ = 1, Hgg κ | = 2.9 Avv κ Observed: | = 0.0 Avv κ Expected: (c) Figure 9. Observed (solid black line) and SM expected (dashed blue line) negative log-likelihood scans for (a) κAgg, (b) κHV V and (c) κAV V coupling parameters using 36.1 fb−1of data at √s = 13 TeV. The horizontal lines indicate the value of the profile likelihood ratio corresponding to the 68% and 95% CL intervals for the parameter of interest, assuming the asymptotic χ2 distribution of the test statistic. vanish. If not stated otherwise, the SM couplings κSM and κHgg described in section 3.2 are fixed to the SM value of one. The BSM changes in the Higgs sector are assumed not to affect the SM background processes. Figure 9shows the observed negative log-likelihood as function of one BSM coupling at a time, together with the expectation for the SM Higgs boson. The corresponding exclusion limits at a 95% confidence level (CL), the best-fit values and the size of the 32 JHEP03(2018)095 BSM coupling Fit Expected Observed Best-fit Best-fit Deviation κBSM configuration conf. inter. conf. inter. ˆκBSM ˆκSM from SM κAgg (κHgg = 1, κSM = 1) [−0.47, 0.47] [−0.68, 0.68] ±0.43 - 1.8σ κHV V (κHgg = 1, κSM = 1) [−2.9, 3.2] [0.8, 4.5] 2.9 - 2.3σ κHV V (κHgg = 1, κSM free) [−3.1, 4.0] [−0.6, 4.2] 2.2 1.2 1.7σ κAV V (κHgg = 1, κSM = 1) [−3.5, 3.5] [−5.2, 5.2] ±2.9 - 1.4σ κAV V (κHgg = 1, κSM free) [−4.0, 4.0] [−4.4, 4.4] ±1.5 1.2 0.5σ Table 10. Expected and observed confidence intervals at 95% CL on the κAgg,κHV V and κAV V coupling parameters, their best-fit values and corresponding compatibility with the SM expectation, as obtained from the negative log-likelihood scans performed with 36.1 fb−1of data at √s = 13 TeV. The coupling κHgg is fixed to the SM value of one in the fit, while the coupling κSM is either fixed to the SM value of one or left as a free parameter of the fit. Fit configuration Best-fit ˆκHV V Best-fit ˆκAV V Best-fit ˆκSM Deviation from SM κHgg = 1, κSM = 1 2.9 ±0.5 - 1.9σ κHgg = 1, κSM free 2.1 ±0.3 1.7 1.2σ Table 11. The best-fit coupling values and corresponding deviation from the SM expectation, as obtained from the two-dimensional κHV V –κAV V negative log-likelihood scans performed with 36.1 fb−1of data at √s = 13 TeV. deviation from the SM are summarized in table 10. The event yields measured in the introduced reconstructed event categories do not provide any sensitivity to the sign of the κAgg and κAV V coupling parameters. On the other hand, event yields are expected to be larger for positive κHV V values compared to the negative ones due to large interference effects with the CP-even SM coupling interactions. Due to the larger number of events observed compared with expectation in the reconstructed VBF-enriched event categories, the best-fit values for the coupling parameters κAgg,κHV V and κAV V differ from zero and deviate from the SM expectation at the level of 1.8σ, 2.3σand 1.4σ, respectively. If the coupling parameter κSM of the SM interaction is left free in the fit, the expected limits on the BSM HV V and AV V couplings decrease by up to 10%. The observed deviation from the SM hypothesis decreases to below 2σ(1σ) for the BSM HV V (AV V ) coupling, since the observed excess of events is at least partially absorbed by a 20% increase of the SM coupling parameter κSM. The best-fit κHV V and κAV V values decrease correspondingly. Due to the mentioned interference effects for CP-even couplings, the expected yields decrease more steeply with decreasing κHV V , so that the increasing κSM value cannot fully compensate for the observed excess. The best-fit κHV V value therefore decreases less than the best-fit κAV V value compared to the fit configuration with κSM = 1. The CP-even and CP-odd BSM couplings to heavy vector bosons are also probed simultaneously in a two-dimensional contour analysis of the negative log-likelihood. The results are shown in figure 10 and summarized in table 11. The best-fit value ˆκHV V obtained from the two-dimensional scan is similar to the one obtained in the one-dimensional scan. The value of ˆκAV V from the two-dimensional scan is 33 JHEP03(2018)095 Avv κ 6−4−2−0 2 4 6 Hvv κ 4− 2− 0 2 4 6 8 10 12 14 Best Fit Observed 95% CL SM SM expected 95% CL ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb = 1 SM κ = 1, Hgg κ = 2.9 Hvv κ | = 0.5, Avv κObserved: | = 0.0 Hvv κ = 0.0, Avv κExpected: (a) Avv κ 6−4−2−0 2 4 6 Hvv κ 4− 2− 0 2 4 6 8 10 12 14 Best Fit Observed 95% CL SM SM expected 95% CL ATLAS 4l→ ZZ* →H -1 13 TeV, 36.1 fb free SM κ = 1, Hgg κ = 1.7 SM κ = 2.1, Hvv κ| = 0.3, Avv κObserved: | = 1.0 SM κ = 0.0, Hvv κ = 0.0, Avv κExpected: (b) Figure 10. Observed (black) and SM expected (blue) contours of the two-dimensional negative log-likelihood at 95% CL for the κHV V and κAV V coupling parameters with 36.1 fb−1of data at √s = 13 TeV. The coupling κHgg is fixed to the SM value of one in the fit. The coupling κSM is (a) fixed to the SM value of one or (b) left as a free parameter of the fit (b). closer to the SM expectation than the corresponding value from the one-dimensional scan. The obtained result is compatible with the SM prediction within 2σ. The coupling parameter κAgg is also probed directly by the cross sections measured in the reduced Stage-1 production bins. The largest sensitivity to this coupling is obtained from the ggF-0jproduction bin. Here one can neglect the impact of the BSM gluon coupling on the BDTggF observable that is based solely on the Higgs boson decay topology. The cross-section dependence on the BSM coupling is parameterized using simulated Mad- Graph5 aMC@NLO samples and fitted to the measured values. The fit results agree with those presented in table 10. 10 Summary The coupling properties of the Higgs boson are studied in the four-lepton decay channel using 36.1 fb−1of LHC pp collision data at √s =13 TeV collected by the ATLAS experiment. The Higgs boson candidate events are categorized into several topologies, providing sensitivity to different production modes in various regions of phase space. Additional BDT discriminants are used to further improve the sensitivity in reconstructed event categories with a sufficiently large number of events. The cross sections times branching ratio for H→ZZ∗decay measured in dedicated production bins are in agreement with the SM predictions. The largest deviation of 2.2σis observed for the VBF production due to an observed excess of events characterized by the presence of at least two jets and a dijet invariant mass above 120 GeV. The inclusive cross 34 JHEP03(2018)095 section in the Higgs boson rapidity range of |yH|<2.5 is measured to be σ·B(H→ZZ∗) = 1.73+0.26 −0.24 pb compared to the SM prediction of 1.34 ±0.09 pb. Results are also interpreted within the κframework with coupling modifiers κVand κF, showing compatibility with the SM. Based on event yields observed in each reconstructed event category, constraints are placed on possible BSM interactions of the Higgs boson within the framework of an effective Lagrangian extension of the SM. The data are shown to be consistent with the SM hypothesis, with the largest deviations of about 2σdue to the excess of observed events in the VBF categories. Exclusion limits are set on the CP-even and CP-odd BSM couplings of the Higgs boson to vector bosons and on the CP-odd BSM Higgs boson coupling to gluons. Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZˇ S, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Sk lodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, R´egion Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. 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Klimek110, A. Klimentov27, R. Klingenberg46,∗, T. Klingl23, T. Klioutchnikova32, F.F. Klitzner102, E.-E. Kluge60a, P. Kluit109, S. Kluth103, E. Kneringer65, E.B.F.G. Knoops88, A. Knue103, A. Kobayashi157, D. Kobayashi73, T. Kobayashi157, M. Kobel47, M. Kocian145, P. Kodys131, T. Koffas31, E. Koffeman109, N.M. K¨ohler103, T. Koi145, M. Kolb60b, I. Koletsou5, A.A. Komar98,∗, T. Kondo69, N. Kondrashova36c, K. K¨oneke51, A.C. K¨onig108, T. Kono69,ae, R. Konoplich112,af , N. Konstantinidis81, B. Konya84, R. Kopeliansky64, S. Koperny41a, A.K. Kopp51, K. Korcyl42, K. Kordas156, A. Korn81, A.A. Korol111,c, I. Korolkov13, E.V. Korolkova141, O. Kortner103, S. Kortner103, T. Kosek131, V.V. Kostyukhin23, A. Kotwal48, A. Koulouris10, A. Kourkoumeli-Charalampidi123a,123b, C. Kourkoumelis9, E. Kourlitis141, V. Kouskoura27, A.B. Kowalewska42, R. Kowalewski172, T.Z. Kowalski41a, 47 JHEP03(2018)095 C. Kozakai157, W. Kozanecki138, A.S. Kozhin132, V.A. Kramarenko101, G. Kramberger78, D. Krasnopevtsev100, M.W. Krasny83, A. Krasznahorkay32, D. Krauss103, J.A. Kremer41a, J. Kretzschmar77, K. Kreutzfeldt55, P. Krieger161, K. Krizka16, K. Kroeninger46, H. Kroha103, J. Kroll129, J. Kroll124, J. Kroseberg23, J. Krstic14, U. Kruchonak68, H. Kr¨uger23, N. Krumnack67, M.C. Kruse48, T. Kubota91, H. Kucuk81, S. Kuday4b, J.T. Kuechler178, S. Kuehn32, A. Kugel60a, F. Kuger177, T. Kuhl45, V. Kukhtin68, R. Kukla88, Y. Kulchitsky95, S. Kuleshov34b, Y.P. Kulinich169, M. Kuna134a,134b, T. Kunigo71, A. Kupco129, T. Kupfer46, O. Kuprash155, H. Kurashige70, L.L. Kurchaninov163a, Y.A. Kurochkin95, M.G. Kurth35a,35d, E.S. Kuwertz172, M. Kuze159, J. Kvita117, T. Kwan172, D. Kyriazopoulos141, A. La Rosa103, J.L. La Rosa Navarro26d, L. La Rotonda40a,40b, F. La Ruffa40a,40b, C. Lacasta170, F. Lacava134a,134b, J. Lacey45, D.P.J. Lack87, H. Lacker17, D. Lacour83, E. Ladygin68, R. Lafaye5, B. Laforge83, T. Lagouri179, S. Lai57, S. Lammers64, W. Lampl7, E. Lan¸con27, U. Landgraf51, M.P.J. Landon79, M.C. Lanfermann52, V.S. Lang45, J.C. Lange13, R.J. Langenberg32, A.J. Lankford166, F. Lanni27, K. Lantzsch23, A. Lanza123a, A. Lapertosa53a,53b, S. Laplace83, J.F. Laporte138, T. Lari94a, F. Lasagni Manghi22a,22b, M. Lassnig32, T.S. Lau62a, A. Laudrain119, P. Laurelli50, W. Lavrijsen16, A.T. Law139, P. Laycock77, T. Lazovich59, M. Lazzaroni94a,94b, B. Le91, O. Le Dortz83, E. Le Guirriec88, E.P. Le Quilleuc138, M. LeBlanc172, T. LeCompte6, F. Ledroit-Guillon58, C.A. Lee27, G.R. Lee34a, S.C. Lee153, L. Lee59, B. Lefebvre90, G. Lefebvre83, M. Lefebvre172, F. Legger102, C. Leggett16, G. Lehmann Miotto32, X. Lei7, W.A. Leight45, M.A.L. Leite26d, R. Leitner131, D. Lellouch175, B. Lemmer57, K.J.C. Leney81, T. Lenz23, B. Lenzi32, R. Leone7, S. Leone126a,126b, C. Leonidopoulos49, G. Lerner151, C. Leroy97, R. Les161, A.A.J. Lesage138, C.G. Lester30, M. Levchenko125, J. Levˆeque5, D. Levin92, L.J. Levinson175, M. Levy19, D. Lewis79, B. Li36a,w, C.-Q. Li36a, H. Li150, L. Li36c, Q. Li35a,35d, Q. Li36a, S. Li48, X. Li36c, Y. Li143, Z. Liang35a, B. Liberti135a, A. Liblong161, K. Lie62c, J. Liebal23, W. Liebig15, A. Limosani152, C.Y. Lin30, K. Lin93, S.C. Lin182, T.H. Lin86, R.A. Linck64, B.E. Lindquist150, A.E. Lionti52, E. Lipeles124, A. Lipniacka15, M. Lisovyi60b, T.M. Liss169,ag, A. Lister171, A.M. Litke139, B. Liu67, H. Liu92, H. Liu27, J.K.K. Liu122, J. Liu36b, J.B. Liu36a, K. Liu88, L. Liu169, M. Liu36a, Y.L. Liu36a, Y. Liu36a, M. Livan123a,123b, A. Lleres58, J. Llorente Merino35a, S.L. Lloyd79, C.Y. Lo62b, F. Lo Sterzo43, E.M. Lobodzinska45, P. Loch7, F.K. Loebinger87, A. Loesle51, K.M. Loew25, T. Lohse17, K. Lohwasser141, M. Lokajicek129, B.A. Long24, J.D. Long169, R.E. Long75, L. Longo76a,76b, K.A. Looper113, J.A. Lopez34b, I. Lopez Paz13, A. Lopez Solis83, J. Lorenz102, N. Lorenzo Martinez5, M. Losada21, P.J. L¨osel102, X. Lou35a, A. Lounis119, J. Love6, P.A. Love75, H. Lu62a, N. Lu92, Y.J. Lu63, H.J. Lubatti140, C. Luci134a,134b, A. Lucotte58, C. Luedtke51, F. Luehring64, W. Lukas65, L. Luminari134a, O. Lundberg148a,148b, B. Lund-Jensen149, M.S. Lutz89, P.M. Luzi83, D. Lynn27, R. Lysak129, E. Lytken84, F. Lyu35a, V. Lyubushkin68, H. Ma27, L.L. Ma36b, Y. Ma36b, G. Maccarrone50, A. Macchiolo103, C.M. Macdonald141, B. Maˇcek78, J. Machado Miguens124,128b, D. Madaffari170, R. Madar37, W.F. Mader47, A. Madsen45, N. Madysa47, J. Maeda70, S. Maeland15, T. Maeno27, A.S. Maevskiy101, V. Magerl51, C. Maiani119, C. Maidantchik26a, T. Maier102, A. Maio128a,128b,128d, O. Majersky146a, S. Majewski118, Y. Makida69, N. Makovec119, B. Malaescu83, Pa. Malecki42, V.P. Maleev125, F. Malek58, U. Mallik66, D. Malon6, C. Malone30, S. Maltezos10, S. Malyukov32, J. Mamuzic170, G. Mancini50, I. Mandi´c78, J. Maneira128a,128b, L. Manhaes de Andrade Filho26b, J. Manjarres Ramos47, K.H. Mankinen84, A. Mann102, A. Manousos32, B. Mansoulie138, J.D. Mansour35a, R. Mantifel90, M. Mantoani57, S. Manzoni94a,94b, L. Mapelli32, G. Marceca29, L. March52, L. Marchese122, G. Marchiori83, M. Marcisovsky129, C.A. Marin Tobon32, M. Marjanovic37, D.E. Marley92, F. Marroquim26a, S.P. Marsden87, Z. Marshall16, M.U.F Martensson168, S. Marti-Garcia170, C.B. Martin113, T.A. Martin173, V.J. Martin49, B. Martin dit Latour15, M. Martinez13,v, 48 JHEP03(2018)095 V.I. Martinez Outschoorn169, S. Martin-Haugh133, V.S. Martoiu28b, A.C. Martyniuk81, A. Marzin32, L. Masetti86, T. Mashimo157, R. Mashinistov98, J. Masik87, A.L. Maslennikov111,c, L.H. Mason91, L. Massa135a,135b, P. Mastrandrea5, A. Mastroberardino40a,40b, T. Masubuchi157, P. M¨attig178, J. Maurer28b, S.J. Maxfield77, D.A. Maximov111,c, R. Mazini153, I. Maznas156, S.M. Mazza94a,94b, N.C. Mc Fadden107, G. Mc Goldrick161, S.P. Mc Kee92, A. McCarn92, R.L. McCarthy150, T.G. McCarthy103, L.I. McClymont81, E.F. McDonald91, J.A. Mcfayden32, G. Mchedlidze57, M.A. McKay43, S.J. McMahon133, P.C. McNamara91, C.J. McNicol173, R.A. McPherson172,o, S. Meehan140, T.J. Megy51, S. Mehlhase102, A. Mehta77, T. Meideck58, K. Meier60a, B. Meirose44, D. Melini170,ah, B.R. Mellado Garcia147c, J.D. Mellenthin57, M. Melo146a, F. Meloni18, A. Melzer23, S.B. Menary87, L. Meng77, X.T. Meng92, A. Mengarelli22a,22b, S. Menke103, E. Meoni40a,40b, S. Mergelmeyer17, C. Merlassino18, P. Mermod52, L. Merola106a,106b, C. Meroni94a, F.S. Merritt33, A. Messina134a,134b, J. Metcalfe6, A.S. Mete166, C. Meyer124, J-P. Meyer138, J. Meyer109, H. Meyer Zu Theenhausen60a, F. Miano151, R.P. Middleton133, S. Miglioranzi53a,53b, L. Mijovi´c49, G. Mikenberg175, M. Mikestikova129, M. Mikuˇz78, M. Milesi91, A. Milic161, D.A. Millar79, D.W. Miller33, C. Mills49, A. Milov175, D.A. Milstead148a,148b, A.A. Minaenko132, Y. Minami157, I.A. Minashvili54b, A.I. Mincer112, B. Mindur41a, M. Mineev68, Y. Minegishi157, Y. Ming176, L.M. Mir13, A. Mirto76a,76b, K.P. Mistry124, T. Mitani174, J. Mitrevski102, V.A. Mitsou170, A. Miucci18, P.S. Miyagawa141, A. Mizukami69, J.U. Mj¨ornmark84, T. Mkrtchyan180, M. Mlynarikova131, T. Moa148a,148b, K. Mochizuki97, P. Mogg51, S. Mohapatra38, S. Molander148a,148b, R. Moles-Valls23, M.C. Mondragon93, K. M¨onig45, J. Monk39, E. Monnier88, A. Montalbano150, J. Montejo Berlingen32, F. Monticelli74, S. Monzani94a,94b, R.W. Moore3, N. Morange119, D. Moreno21, M. Moreno Ll´acer32, P. Morettini53a, S. Morgenstern32, D. Mori144, T. Mori157, M. Morii59, M. Morinaga174, V. Morisbak121, A.K. Morley32, G. Mornacchi32, J.D. Morris79, L. Morvaj150, P. Moschovakos10, M. Mosidze54b, H.J. Moss141, J. Moss145,ai, K. Motohashi159, R. Mount145, E. Mountricha27, E.J.W. Moyse89, S. Muanza88, F. Mueller103, J. Mueller127, R.S.P. Mueller102, D. Muenstermann75, P. Mullen56, G.A. Mullier18, F.J. Munoz Sanchez87, W.J. Murray173,133, H. Musheghyan32, M. Muˇskinja78, A.G. Myagkov132,aj , M. Myska130, B.P. Nachman16, O. Nackenhorst52, K. Nagai122, R. Nagai69,ae, K. Nagano69, Y. Nagasaka61, K. Nagata164, M. Nagel51, E. Nagy88, A.M. Nairz32, Y. Nakahama105, K. Nakamura69, T. Nakamura157, I. Nakano114, R.F. Naranjo Garcia45, R. Narayan11, D.I. Narrias Villar60a, I. Naryshkin125, T. Naumann45, G. Navarro21, R. Nayyar7, H.A. Neal92, P.Yu. Nechaeva98, T.J. Neep138, A. Negri123a,123b, M. Negrini22a, S. Nektarijevic108, C. Nellist57, A. Nelson166, M.E. Nelson122, S. Nemecek129, P. Nemethy112, M. Nessi32,ak, M.S. Neubauer169, M. Neumann178, P.R. Newman19, T.Y. Ng62c, Y.S. Ng17, T. Nguyen Manh97, R.B. Nickerson122, R. Nicolaidou138, J. Nielsen139, N. Nikiforou11, V. Nikolaenko132,aj , I. Nikolic-Audit83, K. Nikolopoulos19, P. Nilsson27, Y. Ninomiya69, A. Nisati134a, N. Nishu36c, R. Nisius103, I. Nitsche46, T. Nitta174, T. Nobe157, Y. Noguchi71, M. Nomachi120, I. Nomidis31, M.A. Nomura27, T. Nooney79, M. Nordberg32, N. Norjoharuddeen122, O. Novgorodova47, M. Nozaki69, L. Nozka117, K. Ntekas166, E. Nurse81, F. Nuti91, K. O’connor25, D.C. O’Neil144, A.A. O’Rourke45, V. O’Shea56, F.G. Oakham31,d, H. Oberlack103, T. Obermann23, J. Ocariz83, A. Ochi70, I. Ochoa38, J.P. Ochoa-Ricoux34a, S. Oda73, S. Odaka69, A. Oh87, S.H. Oh48, C.C. Ohm149, H. Ohman168, H. Oide53a,53b, H. Okawa164, Y. Okumura157, T. Okuyama69, A. Olariu28b, L.F. Oleiro Seabra128a, S.A. Olivares Pino34a, D. Oliveira Damazio27, M.J.R. Olsson33, A. Olszewski42, J. Olszowska42, A. Onofre128a,128e, K. Onogi105, P.U.E. Onyisi11,aa, H. Oppen121, M.J. Oreglia33, Y. Oren155, D. Orestano136a,136b, N. Orlando62b, R.S. Orr161, B. Osculati53a,53b,∗, R. Ospanov36a, G. Otero y Garzon29, H. Otono73, M. Ouchrif137d, F. Ould-Saada121, A. Ouraou138, K.P. Oussoren109, Q. Ouyang35a, M. Owen56, R.E. Owen19, V.E. Ozcan20a, 49 JHEP03(2018)095 N. Ozturk8, K. Pachal144, A. Pacheco Pages13, L. Pacheco Rodriguez138, C. Padilla Aranda13, S. Pagan Griso16, M. Paganini179, F. Paige27, G. Palacino64, S. Palazzo40a,40b, S. Palestini32, M. Palka41b, D. Pallin37, E.St. Panagiotopoulou10, I. Panagoulias10, C.E. Pandini52, J.G. Panduro Vazquez80, P. Pani32, S. Panitkin27, D. Pantea28b, L. Paolozzi52, Th.D. Papadopoulou10, K. Papageorgiou9,s, A. Paramonov6, D. Paredes Hernandez179, A.J. Parker75, M.A. Parker30, K.A. Parker45, F. Parodi53a,53b, J.A. Parsons38, U. Parzefall51, V.R. Pascuzzi161, J.M. Pasner139, E. Pasqualucci134a, S. Passaggio53a, Fr. Pastore80, S. Pataraia86, J.R. Pater87, T. Pauly32, B. Pearson103, S. Pedraza Lopez170, R. Pedro128a,128b, S.V. Peleganchuk111,c, O. Penc129, C. Peng35a,35d, H. Peng36a, J. Penwell64, B.S. Peralva26b, M.M. Perego138, D.V. Perepelitsa27, F. Peri17, L. Perini94a,94b, H. Pernegger32, S. Perrella106a,106b, R. Peschke45, V.D. Peshekhonov68,∗, K. Peters45, R.F.Y. Peters87, B.A. Petersen32, T.C. Petersen39, E. Petit58, A. Petridis1, C. Petridou156, P. Petroff119, E. Petrolo134a, M. Petrov122, F. Petrucci136a,136b, N.E. Pettersson89, A. Peyaud138, R. Pezoa34b, F.H. Phillips93, P.W. Phillips133, G. Piacquadio150, E. Pianori173, A. Picazio89, M.A. Pickering122, R. Piegaia29, J.E. Pilcher33, A.D. Pilkington87, M. Pinamonti135a,135b, J.L. Pinfold3, H. Pirumov45, M. Pitt175, L. Plazak146a, M.-A. Pleier27, V. Pleskot86, E. Plotnikova68, D. Pluth67, P. Podberezko111, R. Poettgen84, R. Poggi123a,123b, L. Poggioli119, I. Pogrebnyak93, D. Pohl23, I. Pokharel57, G. Polesello123a, A. Poley45, A. Policicchio40a,40b, R. Polifka32, A. Polini22a, C.S. Pollard56, V. Polychronakos27, K. Pomm`es32, D. Ponomarenko100, L. Pontecorvo134a, G.A. Popeneciu28d, D.M. Portillo Quintero83, S. Pospisil130, K. Potamianos45, I.N. Potrap68, C.J. Potter30, H. Potti11, T. Poulsen84, J. Poveda32, M.E. Pozo Astigarraga32, P. Pralavorio88, A. Pranko16, S. Prell67, D. Price87, M. Primavera76a, S. Prince90, N. Proklova100, K. Prokofiev62c, F. Prokoshin34b, S. Protopopescu27, J. Proudfoot6, M. Przybycien41a, A. Puri169, P. Puzo119, J. Qian92, G. Qin56, Y. Qin87, A. Quadt57, M. Queitsch-Maitland45, D. Quilty56, S. Raddum121, V. Radeka27, V. Radescu122, S.K. Radhakrishnan150, P. Radloff118, P. Rados91, F. Ragusa94a,94b, G. Rahal181, J.A. Raine87, S. Rajagopalan27, C. 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Zwalinski32 1Department of Physics, University of Adelaide, Adelaide, Australia 2Physics Department, SUNY Albany, Albany NY, United States of America 3Department of Physics, University of Alberta, Edmonton AB, Canada 4 (a)Department of Physics, Ankara University, Ankara; (b)Istanbul Aydin University, Istanbul; (c) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5LAPP, CNRS/IN2P3 and Universit´e Savoie Mont Blanc, Annecy-le-Vieux, France 6High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America 7Department of Physics, University of Arizona, Tucson AZ, United States of America 8Department of Physics, The University of Texas at Arlington, Arlington TX, United States of America 9Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, The University of Texas at Austin, Austin TX, United States of America 12 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 13 Institut de F´ısica d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain 14 Institute of Physics, University of Belgrade, Belgrade, Serbia 15 Department for Physics and Technology, University of Bergen, Bergen, Norway 16 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA, United States of America 53 JHEP03(2018)095 17 Department of Physics, Humboldt University, Berlin, Germany 18 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland 19 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 20 (a)Department of Physics, Bogazici University, Istanbul; (b)Department of Physics Engineering, Gaziantep University, Gaziantep; (d)Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul; (e)Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 21 Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia 22 (a)INFN Sezione di Bologna; (b)Dipartimento di Fisica e Astronomia, Universit`a di Bologna, Bologna, Italy 23 Physikalisches Institut, University of Bonn, Bonn, Germany 24 Department of Physics, Boston University, Boston MA, United States of America 25 Department of Physics, Brandeis University, Waltham MA, United States of America 26 (a)Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b)Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c)Federal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei; (d)Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil 27 Physics Department, Brookhaven National Laboratory, Upton NY, United States of America 28 (a)Transilvania University of Brasov, Brasov; (b)Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; (c)Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi; (d)National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj Napoca; (e)University Politehnica Bucharest, Bucharest; (f)West University in Timisoara, Timisoara, Romania 29 Departamento de F´ısica, Universidad de Buenos Aires, Buenos Aires, Argentina 30 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 31 Department of Physics, Carleton University, Ottawa ON, Canada 32 CERN, Geneva, Switzerland 33 Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America 34 (a)Departamento de F´ısica, Pontificia Universidad Cat´olica de Chile, Santiago; (b)Departamento de F´ısica, Universidad T´ecnica Federico Santa Mar´ıa, Valpara´ıso, Chile 35 (a)Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; (b)Department of Physics, Nanjing University, Jiangsu; (c)Physics Department, Tsinghua University, Beijing 100084; (d)University of Chinese Academy of Science (UCAS), Beijing, China 36 (a)Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Anhui; (b)School of Physics, Shandong University, Shandong; (c)Department of Physics and Astronomy, Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Tsung-Dao Lee Institute, China 37 Universit´e Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France 38 Nevis Laboratory, Columbia University, Irvington NY, United States of America 39 Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark 40 (a)INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)Dipartimento di Fisica, Universit`a della Calabria, Rende, Italy 41 (a)AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow; (b)Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 42 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 43 Physics Department, Southern Methodist University, Dallas TX, United States of America 44 Physics Department, University of Texas at Dallas, Richardson TX, United States of America 45 DESY, Hamburg and Zeuthen, Germany 46 Lehrstuhl f¨ur Experimentelle Physik IV, Technische Universit¨at Dortmund, Dortmund, Germany 47 Institut f¨ur Kern- und Teilchenphysik, Technische Universit¨at Dresden, Dresden, Germany 54 JHEP03(2018)095 48 Department of Physics, Duke University, Durham NC, United States of America 49 SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 50 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 51 Fakult¨at f¨ur Mathematik und Physik, Albert-Ludwigs-Universit¨at, Freiburg, Germany 52 Departement de Physique Nucleaire et Corpusculaire, Universit´e de Gen`eve, Geneva, Switzerland 53 (a)INFN Sezione di Genova; (b)Dipartimento di Fisica, Universit`a di Genova, Genova, Italy 54 (a)E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 55 II Physikalisches Institut, Justus-Liebig-Universit¨at Giessen, Giessen, Germany 56 SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 57 II Physikalisches Institut, Georg-August-Universit¨at, G¨ottingen, Germany 58 Laboratoire de Physique Subatomique et de Cosmologie, Universit´e Grenoble-Alpes, CNRS/IN2P3, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States of America 60 (a)Kirchhoff-Institut f¨ur Physik, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany 61 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 62 (a)Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; (b) Department of Physics, The University of Hong Kong, Hong Kong; (c)Department of Physics and Institute for Advanced Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 63 Department of Physics, National Tsing Hua University, Taiwan, Taiwan 64 Department of Physics, Indiana University, Bloomington IN, United States of America 65 Institut f¨ur Astro- und Teilchenphysik, Leopold-Franzens-Universit¨at, Innsbruck, Austria 66 University of Iowa, Iowa City IA, United States of America 67 Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America 68 Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia 69 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 70 Graduate School of Science, Kobe University, Kobe, Japan 71 Faculty of Science, Kyoto University, Kyoto, Japan 72 Kyoto University of Education, Kyoto, Japan 73 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 74 Instituto de F´ısica La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 75 Physics Department, Lancaster University, Lancaster, United Kingdom 76 (a)INFN Sezione di Lecce; (b)Dipartimento di Matematica e Fisica, Universit`a del Salento, Lecce, Italy 77 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 78 Department of Experimental Particle Physics, Joˇzef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 79 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 80 Department of Physics, Royal Holloway University of London, Surrey, United Kingdom 81 Department of Physics and Astronomy, University College London, London, United Kingdom 82 Louisiana Tech University, Ruston LA, United States of America 83 Laboratoire de Physique Nucl´eaire et de Hautes Energies, UPMC and Universit´e Paris-Diderot and CNRS/IN2P3, Paris, France 84 Fysiska institutionen, Lunds universitet, Lund, Sweden 85 Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain 86 Institut f¨ur Physik, Universit¨at Mainz, Mainz, Germany 87 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 88 CPPM, Aix-Marseille Universit´e and CNRS/IN2P3, Marseille, France 55 JHEP03(2018)095 89 Department of Physics, University of Massachusetts, Amherst MA, United States of America 90 Department of Physics, McGill University, Montreal QC, Canada 91 School of Physics, University of Melbourne, Victoria, Australia 92 Department of Physics, The University of Michigan, Ann Arbor MI, United States of America 93 Department of Physics and Astronomy, Michigan State University, East Lansing MI, United States of America 94 (a)INFN Sezione di Milano; (b)Dipartimento di Fisica, Universit`a di Milano, Milano, Italy 95 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic of Belarus 96 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Republic of Belarus 97 Group of Particle Physics, University of Montreal, Montreal QC, Canada 98 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 99 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 100 National Research Nuclear University MEPhI, Moscow, Russia 101 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 102 Fakult¨at f¨ur Physik, Ludwig-Maximilians-Universit¨at M¨unchen, M¨unchen, Germany 103 Max-Planck-Institut f¨ur Physik (Werner-Heisenberg-Institut), M¨unchen, Germany 104 Nagasaki Institute of Applied Science, Nagasaki, Japan 105 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 106 (a)INFN Sezione di Napoli; (b)Dipartimento di Fisica, Universit`a di Napoli, Napoli, Italy 107 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America 108 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands 109 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands 110 Department of Physics, Northern Illinois University, DeKalb IL, United States of America 111 Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia 112 Department of Physics, New York University, New York NY, United States of America 113 Ohio State University, Columbus OH, United States of America 114 Faculty of Science, Okayama University, Okayama, Japan 115 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK, United States of America 116 Department of Physics, Oklahoma State University, Stillwater OK, United States of America 117 Palack´y University, RCPTM, Olomouc, Czech Republic 118 Center for High Energy Physics, University of Oregon, Eugene OR, United States of America 119 LAL, Univ. Paris-Sud, CNRS/IN2P3, Universit´e Paris-Saclay, Orsay, France 120 Graduate School of Science, Osaka University, Osaka, Japan 121 Department of Physics, University of Oslo, Oslo, Norway 122 Department of Physics, Oxford University, Oxford, United Kingdom 123 (a)INFN Sezione di Pavia; (b)Dipartimento di Fisica, Universit`a di Pavia, Pavia, Italy 124 Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America 125 National Research Centre “Kurchatov Institute” B.P.Konstantinov Petersburg Nuclear Physics Institute, St. Petersburg, Russia 126 (a)INFN Sezione di Pisa; (b)Dipartimento di Fisica E. Fermi, Universit`a di Pisa, Pisa, Italy 127 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States of America 128 (a)Laborat´orio de Instrumenta¸c˜ao e F´ısica Experimental de Part´ıculas - LIP, Lisboa; (b)Faculdade de Ciˆencias, Universidade de Lisboa, Lisboa; (c)Department of Physics, University of Coimbra, Coimbra; (d)Centro de F´ısica Nuclear da Universidade de Lisboa, Lisboa; (e)Departamento de 56